November 2024 arXiv papers — page 122

Naga Sireesha Chinthala, Jenell Lewis, Sravan Vuppalapati, Khiran Kumar Chidambaram Sivaraman

As the debate over the future of transportation continues in the midst of the COVID-19 pandemic as a deepening global crisis, taxi industry seems to be not spared by the quick and disrupting changes that may arise from the pandemic. The impact is relatively higher in major cities because of the high-density population and transportation congestion. In this s

Max M. Chumley, Firas A. Khasawneh

Many dynamical systems are difficult or impossible to model using high fidelity physics based models. Consequently, researchers are relying more on data driven models to make predictions and forecasts. Based on limited training data, machine learning models often deviate from the true system states over time and need to be continually updated as new measurem

Fatemeh Ghaffari, Xuchuang Wang, Jinhang Zuo, Mohammad Hajiesmaili

We study the problem of multi-agent multi-armed bandits with adversarial corruption in a heterogeneous setting, where each agent accesses a subset of arms. The adversary can corrupt the reward observations for all agents. Agents share these corrupted rewards with each other, and the objective is to maximize the cumulative total reward of all agents (and not

Alex Foote

We present neuron embeddings, a representation that can be used to tackle polysemanticity by identifying the distinct semantic behaviours in a neuron's characteristic dataset examples, making downstream manual or automatic interpretation much easier. We apply our method to GPT2-small, and provide a UI for exploring the results. Neuron embeddings are computed

Muzhi Li, Cehao Yang, Chengjin Xu, Xuhui Jiang

The Knowledge Graph Completion~(KGC) task aims to infer the missing entity from an incomplete triple. Existing embedding-based methods rely solely on triples in the KG, which is vulnerable to specious relation patterns and long-tail entities. On the other hand, text-based methods struggle with the semantic gap between KG triples and natural language. Apart f

Zhuohang Yu, Ling An, Yansong Li, Yu Wu

Conventional methods, including Decision Tree (DT)-based methods, have been effective in scientific tasks, such as non-image medical diagnostics, system anomaly detection, and inorganic catalysis efficiency prediction. However, most deep-learning techniques have struggled to surpass or even match this level of success as traditional machine-learning methods.

Kyungmin Son, Kimberly Bowal, L. Mahadevan, Ho-Young Kim

Synthetic active collectives, composed of many nonliving individuals capable of cooperative changes in group shape and dynamics, hold promise for practical applications and for the elucidation of guiding principles of natural collectives. However, the design of collective robotic systems that operate effectively without intelligence or complex control at eit

Carl Marmier, Nico Seegert, Felix Karbstein

We aim at insights about how localization of the background field impacts nonlinear quantum vacuum signatures probed by photons in purely magnetic, electric and crossed fields. The starting point of our study are the one-loop results for the Heisenberg-Euler effective Lagrangian and the photon polarization tensor in quantum electrodynamics (QED) evaluated in

Carlos Collados-Rodriguez, Daniel Westerman Spier, Marc Cheah-Mane, Eduardo Prieto-Araujo

In this paper, frequency dynamics in modern power systems with a high penetration of converter-based generation is analysed. A fundamental analysis of the frequency dynamics is performed to identify the limitations and challenges when the converter penetration is increased. The voltage-source behaviour is found as an essential characteristic of converters to

Marius Weber, Kai Leckron, Luca Haag, Rodrigo Jaeschke-Ubiergo

Altermagnets constitute a new class of magnetic materials that combine properties previously thought to be exclusive to either antiferromagnets or ferromagnets, and have unique properties of their own. In particular, a combination of symmetries connecting magnetic sublattices gives rise to a band spin splitting exhibiting unconventional d, g, or i-wave chara

Andrew Hotnisky, Shubham Kanodia, Jessica Libby-Roberts, Suvrath Mahadevan

We present the discovery of TOI-6303b and TOI-6330b, two massive transiting super-Jupiters orbiting a M0 and a M2 star respectively, as part of the Searching for GEMS survey. These were detected by TESS and then confirmed via ground-based photometry and radial velocity observations with the Habitable-zone Planet Finder (HPF). TOI-6303b has a mass of 7.84 +/-

Di Xu, Yang Yang, Hengjie Liu, Qihui Lyu

Computed tomography (CT) provides high spatial resolution visualization of 3D structures for scientific and clinical applications. Traditional analytical/iterative CT reconstruction algorithms require hundreds of angular data samplings, a condition that may not be met in practice due to physical and mechanical limitations. Sparse view CT reconstruction has b

Qianru Yang, Haotian Wu, Hao Hu, F. J. García-Vidal

Superfocusing confines light within subwavelength structures, breaking the diffraction limit. Structures with spatial singularities, such as metallic cones, are crucial to enable nanoscale focusing, leading to significant advancements in nanophotonics, sensing, and imaging. Here, we exploit the spatiotemporal analogue of the wedge structure, i.e. a dielectri

Lucas Souza e Silva, Luis Rodrigues

This paper presents for the first time an approach to minimize direct operational costs (DOC) for all-electric aircraft during the climb phase, introducing a time-varying cost index (CI). The CI is modeled as a dynamic parameter commanded by Air Traffic Control (ATC), allowing the aircraft to maintain a constant airspeed throughout the climb, while respectin

M. Espinoza Ortiz, L. Guaita, R. Demarco, A. Calabró

Context: Understanding galaxy evolution in dense environments, particularly proto-clusters, is crucial for studying mechanisms driving star formation and quenching. Aims: This study examines how two proto-cluster over-densities at 3 < z < 4 impact star formation rate (SFR), stellar mass, and morphology, focusing on quenched galaxies. Methods: We identified p

Michael A. Sauer, Souvik Mondal, Brandon Neff, Sthitadhi Maiti

Protein function does not solely depend on structure but often relies on dynamical transitions between distinct conformations. Despite this fact, our ability to characterize or predict protein dynamics is substantially less developed compared to state-of-the-art protein structure prediction. Molecular simulations provide unique opportunities to study protein

Rochelle E. Tractenberg, Andrew C. Lee, Rachelle DeCoste

We outline a new tool that can promote coherence within and across higher education mathematics courses by focusing on problem-solving: the Mathematical Problem-Solving Pipeline or MPSP. The MPSP can be used for teaching mathematics and mathematical reasoning authentically. It can be used across courses to develop problem solving skills that can be generaliz

René Ledesma-Alonso, Benjamin Lalanne, Jesús Israel Morán-Cortés, Martín Aguilar-González

A new model to follow the complete evolution of a drop in Leidenfrost state is presented in this work. The main ingredients of the phenomenon were considered, including: 1) the shape and weight of a sessile drop, according to its size, compared to the capillary length, using the Young-Laplace equation; 2) the evaporation at the entire surface of the drop, du

Mathew S. Madhavacheril

The standard $\Lambda$CDM cosmological model informed by cosmic microwave background (CMB) anisotropies makes a precise prediction for the growth of matter density fluctuations over cosmic time on linear scales. A variety of cosmological observables offer independent and complementary ways of testing this prediction, but results have been mixed, with many co

Gary Hoppenworth, Yinzhan Xu, Zixuan Xu

We study distance preservers, hopsets, and shortcut sets in $n$-node, $m$-edge directed graphs, and show improved bounds and new reductions for various settings of these problems. Our first set of results is about exact and approximate distance preservers. We give the following bounds on the size of directed distance preservers with $p$ demand pairs: 1) $\ti

Yunzhe Zhou, Giles Hooker

Integral projection models (IPMs) are widely used to study population growth and the dynamics of demographic structure (e.g. age and size distributions) within a population.These models use data on individuals' growth, survival, and reproduction to predict changes in the population from one time point to the next and use these in turn to ask about long-term

Bingran Wang, Min Sung Kim, Taewoong Yoon, Dasom Lee

Careful design of semiconductor manufacturing equipment is crucial for ensuring the performance, yield, and reliability of semiconductor devices. Despite this, numerical optimization methods are seldom applied to optimize the design of such equipment due to the difficulty of obtaining accurate simulation models. In this paper, we address a practical and indu

Dinesh Srivasthav P, Badri Narayan Subudhi

Pioneering advancements in artificial intelligence, especially in genAI, have enabled significant possibilities for content creation, but also led to widespread misinformation and false content. The growing sophistication and realism of deepfakes is raising concerns about privacy invasion, identity theft, and has societal, business impacts, including reputat

Siheng Li, Cheng Yang, Zesen Cheng, Lemao Liu

Large language models (LLMs) have achieved substantial progress in processing long contexts but still struggle with long-context reasoning. Existing approaches typically involve fine-tuning LLMs with synthetic data, which depends on annotations from human experts or advanced models like GPT-4, thus restricting further advancements. To address this issue, we

Xiaolong Han

Bourgain used the Rudin-Shapiro sequences to construct a basis of uniformly bounded holomorphic functions on the unit sphere in C2. They are also spherical harmonics (i.e., Laplacian eigenfunctions) on S3 in R4. In this paper, we identify the semiclassical measure associated to these spherical harmonics by a measure supported on the family of Clifford tori i

Philippe Bergault, Louis Bertucci, David Bouba, Olivier Guéant

In this paper, we introduce a novel framework to model the exchange rate dynamics between two intrinsically linked cryptoassets, such as stablecoins pegged to the same fiat currency or a liquid staking token and its associated native token. Our approach employs multi-level nested Ornstein-Uhlenbeck (OU) processes, for which we derive key properties and devel

Yangge Li, Benjamin C Yang, Sayan Mitra

This paper addresses the problem of visual target tracking in scenarios where a pursuer may experience intermittent loss of visibility of the target. The design of a Switched Visual Tracker (SVT) is presented which aims to meet the competing requirements of maintaining both proximity and visibility. SVT alternates between a visual tracking mode for following

Y. Mahmoud, J. Kawamura, M. T. Hussein, H. Abdallah

This analysis focuses on probing the lepton portal dark matter using Monte Carlo simulated samples from electron-positron collisions at the International Linear Collider (ILC) of 500 GeV center of mass energy with an integrated luminosity of 1000 fb$^{-1}$. The study examines a benchmark scenario where the dark matter is a scalar particle produced as a daugh

Jamil Tahir-Kheli

In 1990, the Millis, Monien, and Pines (MMP) model and its improvement, the Zha, Barzykin, and Pines (ZBP) model in 1996, emerged as a realistic explanation of the cuprate NMR. These two models assume a single electronic component, translational symmetry, and that the electrons simultaneously have aspects of localized antiferromagnetic (AF) spins and delocal

Davin Choo, Chandler Squires, Arnab Bhattacharyya, David Sontag

Accurate estimates of causal effects play a key role in decision-making across applications such as healthcare, economics, and operations. In the absence of randomized experiments, a common approach to estimating causal effects uses \textit{covariate adjustment}. In this paper, we study covariate adjustment for discrete distributions from the PAC learning pe

Shreya K. Rajagopal, Thad A. Polk

Exposure therapy, a standard treatment for anxiety disorders, relies on fear extinction. However, extinction recall is often limited to the spatial and temporal context in which extinction is learned, leading to fear relapse in new settings or after delays. Animal studies offer insights into fear extinction in humans. Computational models that integrate thes

Kevin O'Bryant

Let $SPP(n)$ be the set $\left\{\big(|A+A|,|A A|\big) : A\subseteq {\mathbb N}, |A|=n\right\}$ of sum-product pairs, where $A+A$ is the sumset $\{a+b : a,b\in A\}$ and $A A$ is the product set $\{ab:a,b\in A\}$. We construct a dataset consisting of 1162868 sets whose sum-product pairs are at least $84\%$ of $SPP(n)$ for each $n\le 32$. Notably, we do **not**

Vitaly Vanchurin

We establish a duality relation between Hamiltonian systems and neural network-based learning systems. We show that the Hamilton's equations for position and momentum variables correspond to the equations governing the activation dynamics of non-trainable variables and the learning dynamics of trainable variables. The duality is then applied to model various

R. Vishnupriya, R. Rajkumar

The properties of a hypergraph explored through the spectrum of its unified matrix was made by the authors in [26]. In this paper, we introduce three different hypergraph matrices: unified Laplacian matrix, unified signless Laplacian matrix, and unified normalized Laplacian matrix, all defined using the unified matrix. We show that these three matrices of a

Ryan Posh, Shenggao Li, Patrick Wensing

Recognizing and identifying human locomotion is a critical step to ensuring fluent control of wearable robots, such as transtibial prostheses. In particular, classifying the intended locomotion mode and estimating the gait phase are key. In this work, a novel, interpretable, and computationally efficient algorithm is presented for simultaneously predicting l

Samuel J. Bell, Mariano Coria Meglioli, Megan Richards, Eduardo Sánchez

Text toxicity detection systems exhibit significant biases, producing disproportionate rates of false positives on samples mentioning demographic groups. But what about toxicity detection in speech? To investigate the extent to which text-based biases are mitigated by speech-based systems, we produce a set of high-quality group annotations for the multilingu

Junsong Cang, Andrei Mesinger, Steven G. Murray, Daniela Breitman

In 2018 the EDGES experiment claimed the first detection of the global cosmic 21cm signal, which featured an absorption trough centered around $z \sim 17$ with a depth of approximately -500mK. This amplitude is deeper than the standard prediction (in which the radio background is determined by the cosmic microwave background) by a factor of two and potential

Nadav Benedek, Matan Levy, Mahmood Sharif

Neural networks have shown remarkable performance in various tasks, yet they remain susceptible to subtle changes in their input or model parameters. One particularly impactful vulnerability arises through the Bit-Flip Attack (BFA), where flipping a small number of critical bits in a model's parameters can severely degrade its performance. A common technique

Elena Atanassova Lawrie, José Nicolás Orce

Theoretical models often invoke triaxial nuclear shapes to explain elusive collective phenomena, but such assumptions are usually difficult to confirm experimentally. The only direct measurements of the nuclear axial asymmetry $\gamma$ is based on rotational invariants of zero-coupled products of the electric-quadrupole (E2) operator, the Kumar-Cline sum rul

Jarod Tall, Torsten Weber, Juan Diego Urbina, Klaus Richter

We show the late time, or $\tau-$scaled, limit of the canonical spectral form factor (SFF) in unorientable JT gravity agrees with universal random matrix theory (RMT) up to genus one in the topological expansion, establishing a key signature of quantum chaos for the time-reversal symmetric case. The loop equations for an orthogonal matrix model with spectral

Priyanka Patel, Michael J. Black

We address the challenge of accurate 3D human pose and shape estimation from monocular images. The key to accuracy and robustness lies in high-quality training data. Existing training datasets containing real images with pseudo ground truth (pGT) use SMPLify to fit SMPL to sparse 2D joint locations, assuming a simplified camera with default intrinsics. We ma

Shih-Ying Yeh, Yi Li, Sang-Hyun Park, Giyeong Oh

TIPO (Text-to-Image Prompt Optimization) introduces an efficient approach for automatic prompt refinement in text-to-image (T2I) generation. Starting from simple user prompts, TIPO leverages a lightweight pre-trained model to expand these prompts into richer and more detailed versions. Conceptually, TIPO samples refined prompts from a targeted sub-distributi

Karanpreet Singh, Gabe Wilson, James A. H. Stotz

Through the use of strain and induced piezoelectric fields, surface acoustic waves have been shown to control quantum information processes, such as single photon emission and the coherent transport of electron spins. Regarding the latter, systems using plane surface waves have provided suitable demonstration systems, but to build complexity, more control ov

E. Veraldi, L. Vallini, F. Pozzi, F. Esposito

In this work, we devise a model for estimating UV and optical line emission (i.e., CIII] $1909$A, H$\beta$, [OIII] $5007$A, H$\alpha$, [NII] $6583$A) tracing HII regions in the interstellar medium (ISM) of galaxies at $z\sim4-6$ from the ALMA Large Programme ALPINE. The aim is to investigate the impact of binary stars in the stellar population along with an

Sidharth Kaliappan, Abhay Sheel Anand, Koustuv Saha, Ravi Karkar

We explore some of the existing research in HCI around technology for older adults and examine the role of LLMs in enhancing it. We also discuss the digital divide and emphasize the need for inclusive technology design. At the same time, we also surface concerns regarding privacy, security, and the accuracy of information provided by LLMs, alongside the impo

Chuyu Zhou, Tianyu Li, Chenxi Lan, Rongyu Du

Soft- and hard-constrained Physics Informed Neural Networks (PINNs) have achieved great success in solving partial differential equations (PDEs). However, these methods still face great challenges when solving the Navier-Stokes equations (NSEs) with complex boundary conditions. To address these challenges, this paper introduces a novel complementary scheme c

Chenan Wei, Liu Yang, Qing-Dong Jiang

Topological phases in frustrated quantum magnetic systems have captivated researchers for decades, with the chiral spin liquid (CSL) standing out as one of the most compelling examples. Featured by long-range entanglement, topological order, and exotic fractional excitations, the CSL has inspired extensive exploration for practical realizations. In this work

Mark A. Siebert, Raghvendra Sahai, Samantha Scibelli, Anthony J. Remijan

Binaries are known to play a key role in the mass loss and dynamical environments of evolved stars. Stellar and sub-stellar companion interactions produce complex wind morphologies including rotating/expanding disks, bipolar outflows, and spiral wind patterns; however, the connection between these many structures and the gas phase chemistry they harbor is no

Gopal Chandra Santra, Sudipto Singha Roy, Daniel J. Egger, Philipp Hauke

The ability to generate bipartite entanglement in quantum computing technologies is widely regarded as pivotal. However, the role of genuinely multipartite entanglement is much less understood than bipartite entanglement, particularly in the context of solving complicated optimization problems using quantum devices. It is thus crucial from both the algorithm

Jonathan Lin

Coupled-mode theory (CMT) is a powerful tool for simulating near-harmonic systems. In telecommunications, variations of the theory have been used extensively to study waveguides, both analytically and through numerical modelling. Analogous mathematical techniques to the CMT are also widely used in quantum mechanics. The purpose of this work is to collect dif

Hyungjin Joo, M. James Jee, Juhan Kim, Jaehyun Lee

We investigate the formation history of intrahalo light (IHL) using the high-resolution (~1 kpc), large-scale (~Gpc) cosmological hydrodynamical simulation, Horizon Run 5 (HR5). IHL particles are identified by carefully considering both their binding energies and positions with respect to the tidal radii of individual galaxies. By analyzing more than 1,200 g

Yuh Tsunetoe, Ramesh Narayan, Angelo Ricarte

We investigate how magnetic field variations around accreting black holes on event horizon scales affect the morphology of magnetically-driven jet on larger scales. By performing radiative transfer calculations on general relativistic magnetohydrodynamics simulations, we find that temporal variation in the magnetic flux on the event horizon and the jet power

Jonathan Lin, Michael P. Fitzgerald

We present several nonlinear wavefront sensing techniques for few-mode sensors, all of which are empirically calibrated and agnostic to the choice of wavefront sensor. The first class of techniques involves a straightforward extension of the linear phase retrieval scheme to higher order; the resulting Taylor polynomial can then be solved using the method of

Thiago de L. Campos, C. Molina, J. A. S. Lima

This work investigates the evaporation of black holes immersed in a de Sitter environment, using the Vaidya-de Sitter spacetime. The role of cosmological observers is highlighted in the development and Hayward thermodynamics for non-stationary geometries is employed in the description of the compact objects. The results of the proposed dynamical model are co

Hamsa Padmanabhan

Hydrogen, the most abundant element in the Universe, has traditionally been used to investigate astrophysical processes within and around our own Galaxy. In its chemically neutral, atomic form (known as HI in the astronomical literature), it has tremendous potential today as a tool for precision cosmology and testing theories of fundamental physics. Cosmolog

Arghya Choudhury, Sourav Mitra, Arpita Mondal, Subhadeep Mondal

In this article, we probe the trilinear $R$-parity violating (RPV) supersymmetric (SUSY) scenarios with specific nonzero interactions in the light of neutrino oscillation, Higgs, and flavor observables. We attempt to fit the set of observables using a state-of-the-art Markov Chain Monte Carlo (MCMC) setup and study its impact on the model parameter space. Ou

Jared Siegel, Peter Melchior

A notorious problem in astronomy is the recovery of the true shape and spectral energy distribution (SED) of a galaxy despite attenuation by interstellar dust embedded in the same galaxy. This problem has been solved for a few hundred nearby galaxies with exquisite data coverage, but these techniques are not scalable to the billions of galaxies soon to be ob

Ties-A. Ohst, Shijun Zhang, Hai Chau Nguyen, Martin Plávala

Quantum memories are a crucial precondition in many protocols for processing quantum information. A fundamental problem that illustrates this statement is given by the task of channel discrimination, in which an unknown channel drawn from a known random ensemble should be determined by applying it for a single time. In this paper, we characterise the quality

Alexander F. Jercher, José Diogo Simão, Sebastian Steinhaus

We construct an effective cosmological spin-foam model for a (2+1) dimensional spatially flat universe, discretized on a hypercubical lattice, containing both space- and time-like regions. Our starting point is the recently proposed coherent state spin-foam model for (2+1) Lorentzian quantum gravity. The full amplitude is assumed to factorize into single ver

Yan Zhang, Hanqi Pi, Jiaxuan Liu, Wangqian Miao

We develop a comprehensive method to construct analytical continuum models for moir\'e systems directly from first-principle calculations without any parameter fitting. The core idea of this method is to interpret the terms in the continuum model as a basis, allowing us to determine model parameters as coefficients of this basis through Gram-Schmidt orthogon

Zhi-Qiang Gao, Congjun Wu

We construct a (1+1)-dimension continuum model of 4-component fermions incorporating the exceptional Lie group symmetry $G_2$. Four gapped and five gapless phases are identified via the one-loop renormalization group analysis. The gapped phases are controlled by four different stable $SO(8)$ Gross-Neveu fixed points, among which three exhibit an emergent tri

Krishan Chand, Gopal-Krishna, Hum Chand

We report a novel pilot project to characterise intra-night optical variability (INOV) of an extremely rare type of quasar, which has recently been caught in the act of transiting from a radio-quiet to radio-loud state, on a decadal time scale. Such rare transitions may signify a recurrence, or conceivably the first switch-on of jet activity in optically lum

Chuan Chen, Inti Sodemann Villadiego

We compute the spectra of anyon quasiparticles in all three super-selection sectors of the Kitaev model (i.e., visons, fermions and bosons), perturbed by a Zeeman field away from its exactly solvable limit, to gain insights on the competition of its non-abelian spin-liquid with other nearby phases, such as the mysterious intermediate state observed in the an

R. Kondapally, P. N. Best, K. J. Duncan, H. J. A. Röttgering

We characterise the co-evolution of radio-loud AGN and their galaxies by mapping the dependence of radio-loud AGN activity on stellar mass and star-formation rate (SFR) across cosmic time (out to $z \sim 1.5$). Deep LOFAR radio observations are combined with large galaxy samples to study the incidence of radio-loud AGN across the galaxy population; the AGN a

J. P. Breuer, N. Werner, T. Plšek, F. Mernier

We present the results of Chandra and XMM-Newton X-ray imaging and spatially resolved spectroscopy, as well as new MUSTANG2 90 GHz observations of the thermal Sunyaev-Zeldovich effect from MACS J0717.5+3745, an intermediate redshift ($z=0.5458$) and exceptionally massive ($3.5\pm0.6\times10^{15}$ M$_\odot$) Frontier Fields cluster experiencing multiple merge

Habib Rostami, Nitay Ben-Shachar, Sergej Moroz, Johannes Hofmann

Degenerate two-dimensional electron liquids are theoretically established to possess two vastly distinct collisional electron mean free paths, where even-parity deformations of the Fermi surface are hydrodynamic with a short collisional mean free path but odd-parity deformations remain near ballistic (known as the "tomographic" transport regime). Predicted s

Ferruccio Feruglio, Robert Ziegler

We study a class of supersymmetric models where the strong CP problem is solved through spontaneous CP violation, carried out by a complex scalar field that determines the Yukawa couplings of the theory. Assuming that one real component of this field - the CPon - is light, we examine the conditions under which it provides a viable Dark Matter candidate. The

Yingjie Cheng, Mauro Giavalisco, Bren E. Backhaus, Rachana Bhatawdekar

Over the past decades, a population of galaxies invisible in optical/near-infrared, but bright at longer wavelengths, have been identified through color selections. These so-called optically faint/dark galaxies are considered to be massive quiescent galaxies or highly dust-attenuated galaxies. Having the entire galaxy obscured by dust, however, is likely an

Abinaya Swaruba Rajamuthukumar, Evan B. Bauer, Stephen Justham, Rüdiger Pakmor

Compact binaries containing hot subdwarfs and white dwarfs have the potential to evolve into a variety of explosive transients. These systems could also explain hypervelocity runaway stars such as US 708. We use the detailed binary evolution code MESA to evolve hot subdwarf and white dwarf stars interacting in binaries. We explore their evolution towards dou

Simon Holz, Martin Hoferichter, Bai-Long Hoid, Bastian Kubis

Next to the $\pi^0$ pole, $\eta$ and $\eta'$ intermediate states give rise to the leading singularities of the hadronic light-by-light tensor, resulting in sizable contributions to the anomalous magnetic moment of the muon $a_\mu$. The strength of the poles is determined by the respective transition form factors (TFFs) to two (virtual) photons. We present a

Manuel A. Buen-Abad, Zackaria Chacko, Ina Flood, Can Kilic

We present a new class of interacting dark sector models that can address the Hubble tension. Interacting dark radiation (DR) has previously been put forward as a solution to the problem, but this proposal is disfavored by the high-$\ell$ cosmic microwave background (CMB) data. We modify this basic framework by introducing a subcomponent of dark matter (DM)

Stefano O. Souza, Marica Valentini, Cristina Chiappini, Angeles Pérez-Villegas

The Galactic bulge hosts the Milky Way's oldest stars, possibly coming from disrupted globular clusters (GCs) or the bulge's primordial building blocks, making these stars witnesses to the Galaxy's early chemical enrichment. The Galactic bar currently dominates the bulge's region, altering the orbits of objects formed before its formation and complicating th

Adam J. McRoberts, Chris Hooley, A. G. Green

The $J_1$-$J_2$ spin chain is one of the canonical models of quantum magnetism, and has long been known to host a critical antiferromagnetic phase with power-law decay of spin correlations. We show in this Letter that there are, in fact, \textit{two} distinct critical antiferromagnetic phases, where the roles of the local dimer field and its dual field are i

Yubo Su, Dong Lai

The stellar obliquity of a planetary system is often used to help constrain the system's formation and evolution. One of the mechanisms to reorient the stellar spin involves a secular resonance crossing due to the dissipation of the protoplanetary disk when the system also has an inclined, distant ($\sim 300\;\mathrm{AU}$) binary companion. This mechanism is

Kai Klocke, Yue Liu, Gábor B. Halász, Jason Alicea

Topological quantum computation relies on control of non-Abelian anyons for inherently fault-tolerant storage and processing of quantum information. By now, blueprints for topological qubits are well developed for electrically active topological superconductor and fractional quantum Hall platforms. We leverage recent insights into the creation and detection

Ward S. Howard, Meredith A. MacGregor, Adina D. Feinstein, Laura D. Vega

Ultraviolet flare emission can drive photochemistry in exoplanet atmospheres and even serve as the primary source of uncertainty in atmospheric retrievals. Additionally, flare energy budgets are not well-understood due to a paucity of simultaneous observations. We present new near-UV (NUV) and optical observations of flares from three M dwarfs obtained at 20

Archisman Panigrahi, Ajesh Kumar

We investigate the spontaneous breaking of subsystem symmetry in a stack of two-dimensional Fermi liquid metals, each maintaining a subsystem number conservation symmetry, driven by interlayer exciton condensation. The resulting Goldstone modes in this broken symmetry phase couple to the quasiparticle current perpendicular to the layers. This coupling, which

David K. Kolchmeyer, Hong Liu

We construct algebras of diff-invariant observables in a global de Sitter universe with two observers and a free scalar QFT in two dimensions. We work in the strict $G_N \rightarrow 0$ limit, but allow the observers to have an order one mass in cosmic units. The observers are fully quantized. In the limit when the observers have infinite mass and are localiz

Elisa Grilli, Marta Orselli, David Pereñiguez, Daniele Pica

Next-generation low-frequency interferometers are expected to detect binary systems near supermassive black holes, where tidal effects can alter significantly the motion of the binary. This motivates a broader investigation of how external gravitational fields influence the dynamics of physical systems. In this work, we consider a charged black hole binary s

Ivan Lopes, Jean-François Lalonde, Raoul de Charette

In this paper, we first propose a novel method for transferring material transformations across different scenes. Building on disentangled Neural Radiance Field (NeRF) representations, our approach learns to map Bidirectional Reflectance Distribution Functions (BRDF) from pairs of scenes observed in varying conditions, such as dry and wet. The learned transf

Dominic Bergeron

The fermionic many-body problem in the strong correlation regime is notoriously difficult to tackle. In a previous work (Phys. Rev. B 101, 045109 (2020)), we have proposed to extend the single-reference coupled-cluster (SRCC) method to the strong correlation regime using low-rank tensor decompositions (LRTD) to express the cluster operator, without truncatin

Zhiyuan Guo, Bhavin Joshi, Chris. W. Walter, M. A. Troxel

We investigate the capability of the \textit{Nancy Grace Roman Space Telescope's (Roman)} Wide-Field Instrument (WFI) G150 slitless grism to detect red, quiescent galaxies based on the current reference survey. We simulate dispersed images for \textit{Roman} reference High-Latitude Spectroscopic Survey (HLSS) and analyze two-dimensional spectroscopic data us

Rahul Ravishankar, Zeeshan Patel, Jathushan Rajasegaran, Jitendra Malik

In this paper, we argue that iterative computation with diffusion models offers a powerful paradigm for not only generation but also visual perception tasks. We unify tasks such as depth estimation, optical flow, and amodal segmentation under the framework of image-to-image translation, and show how diffusion models benefit from scaling training and test-tim

Yushi Lan, Shangchen Zhou, Zhaoyang Lyu, Fangzhou Hong

While 3D content generation has advanced significantly, existing methods still face challenges with input formats, latent space design, and output representations. This paper introduces a novel 3D generation framework that addresses these challenges, offering scalable, high-quality 3D generation with an interactive Point Cloud-structured Latent space. Our fr

Wolfgang Rolke

This article describes the R package moodlequizR, which allows the user to easily create fully randomized quizzes and exams for Moodle, or indeed any online assessment platform that uses XML files for importing questions. In such a quiz the students are presented with the essentially same problem, but with various parts sufficiently different to make cheatin

Antonio Racioppi

We propose a new class of inflationary attractors in metric-affine gravity. Such class features a non-minimal coupling $\tilde\xi \, \Omega(\phi)$ with the Holst invariant $\tilde{\cal R}$ and an inflaton potential proportional to $\Omega(\phi)^2$. The attractor behaviour of the class takes place with two combined strong coupling limits. The first limit is r

Žiga Krajnik, Enej Ilievski, Tomaž Prosen, Benjamin J. A. Héry

We introduce classical many-body dynamics on a one-dimensional lattice comprising local two-body maps arranged on discrete space-time mesh that serve as discretizations of Hamiltonian dynamics with arbitrarily time-varying coupling constants. Time evolution is generated by passing an auxiliary degree of freedom along the lattice, resulting in a `fishnet' cir

Bryce T. Bolin, Larry Denneau, Laura-May Abron, Robert Jedicke

Minimoons are asteroids that become temporarily captured by the Earth-Moon system. We present the discovery of 2024 PT$_5$, a minimoon discovered by the Asteroid Terrestrial-impact Last Alert System (ATLAS) Sutherland telescope on 2024 August 7. The minimoon with heliocentric semi-major axis, $a$$\sim$1.01 au, and perihelion, $q$$\sim$0.99 au, became capture

Juanhui Li, Sreyashi Nag, Hui Liu, Xianfeng Tang

In real-world NLP applications, Large Language Models (LLMs) offer promising solutions due to their extensive training on vast datasets. However, the large size and high computation demands of LLMs limit their practicality in many applications, especially when further fine-tuning is required. To address these limitations, smaller models are typically preferr

Anoop Cherian, Radu Corcodel, Siddarth Jain, Diego Romeres

Most learning-based approaches to complex physical reasoning sidestep the crucial problem of parameter identification (e.g., mass, friction) that governs scene dynamics, despite its importance in real-world applications such as collision avoidance and robotic manipulation. In this paper, we present LLMPhy, a black-box optimization framework that integrates l

Jan Figgener, Jakob Bors, Matthias Kuipers, Felix Hildenbrand

A battery's open circuit voltage (OCV) curve can be seen as its electrochemical signature. Its shape and age-related shift provide information on aging processes and material composition on both electrodes. However, most OCV analyses have to be conducted in laboratories or specified field tests to ensure suitable data quality. Here, we present a method that

Dymitr Ruta, Corrado Mio, Ernesto Damiani

Trees continue to fascinate with their natural beauty and as engineering masterpieces optimal with respect to several independent criteria. Pythagorean tree is a well-known fractal design that realistically mimics the natural tree branching structures. We study various types of Pythagorean-like fractal trees with different shapes of the base, branching angle

Orestis Papadopoulos, Andreas Schmitt

Cold and dense matter may break rotational symmetry spontaneously and thus form an anisotropic phase in the interior of neutron stars. We consider the concrete example of an anisotropic chiral condensate in the form of a chiral density wave. Employing a nucleon-meson model and taking into account fermionic vacuum fluctuations, we improve and extend previous

M. Adrover, M. Babicz, L. Baudis, Y. Biondi

Xenoscope is a demonstrator for a next-generation xenon-based observatory for astroparticle physics, as proposed by the XLZD (XENON-LUX-ZEPLIN-DARWIN) collaboration. It houses a 2.6 m tall, two-phase xenon time projection chamber (TPC), in a cryostat filled with $\sim$ 360 kg of liquid xenon. The main goals of the facility are to demonstrate electron drift i

S. K. Lander

We present the first model aimed at understanding how the Meissner effect in a young neutron star affects its macroscopic magnetic field. In this model, field expulsion occurs on a dynamical timescale, and is realised through two processes that occur at the onset of superconductivity: fluid motions causing the dragging of field lines, followed by magnetic re

S. K. Lander, K. N. Gourgouliatos, Z. Wadiasingh, D. Antonopoulou

Shortly after a neutron star is born, the protons in its core begin to form a superconductor. In terrestrial materials, the hallmark of superconductivity is an associated expulsion of magnetic flux, but whether this expulsion process can be effective in neutron stars remains an open question -- one with major implications for the phenomenology of pulsars and

Lucius E. J. Bynum, Kyunghyun Cho

In this work, we present sequence-driven structural causal models (SD-SCMs), a framework for specifying causal models with user-defined structure and language-model-defined mechanisms. We characterize how an SD-SCM enables sampling from observational, interventional, and counterfactual distributions according to the desired causal structure. We then leverage

Aditya Sanghi, Aliasghar Khani, Pradyumna Reddy, Arianna Rampini

Large-scale 3D generative models require substantial computational resources yet often fall short in capturing fine details and complex geometries at high resolutions. We attribute this limitation to the inefficiency of current representations, which lack the compactness required to model the generative models effectively. To address this, we introduce a nov

Masaru Hongo, Noriyuki Sogabe, Mikhail A. Stephanov, Ho-Ung Yee

We study the hydrodynamic theories with approximate symmetries in the recently developed effective action approach on the Schwinger-Keldysh (SK) contour. We employ the method of spurious symmetry transformation for small explicit symmetry-breaking parameters to systematically constrain symmetry-breaking effects in the non-equilibrium effective action for hyd

Miguel Fuentes, Juan Pablo Cárdenas, Gastón Olivares, Eric Rasmussen

Resilience in social systems is crucial for mitigating the impacts of crises, such as climate change, which poses an existential threat to communities globally. As disasters become more frequent and severe, enhancing community resilience has become imperative. This study introduces a cutting-edge framework, quantitative network-based modeling called Complex